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Exact Bayesian and Fiducial Limits for the Mean of Lognormal Distribution

Exact Bayesian and Fiducial Limits for the Mean of Lognormal Distribution
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摘要 In this paper, the exact Bayesian limits, taking conjugate and noninformative prior distribution, and the exact fiducial limits for the mean of the lognormal distribution are presented. They can be found iteratively by one-dimension integral on a finite interval. The new algorithm is very convenient and with high accuracy. It can meet the practical engineering need excellently. However, the primitive algorithm is rather cumbersome. By the way, the very close approximate limits with a simple algorithm are derived. They can be applied immediately to engineering. Otherwise, they can also be used as a search interval to find the root of equation for the exact limits. In this paper, the exact Bayesian limits, taking conjugate and noninformative prior distribution, and the exact fiducial limits for the mean of the lognormal distribution are presented. They can be found iteratively by one-dimension integral on a finite interval. The new algorithm is very convenient and with high accuracy. It can meet the practical engineering need excellently. However, the primitive algorithm is rather cumbersome. By the way, the very close approximate limits with a simple algorithm are derived. They can be applied immediately to engineering. Otherwise, they can also be used as a search interval to find the root of equation for the exact limits.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1994年第2期41-46,共6页 系统工程与电子技术(英文版)
关键词 ALGORITHMS Approximation theory Engineering research Failure analysis Integral equations INTEGRATION Iterative methods Materials testing Reliability theory Service life Statistical tests Algorithms Approximation theory Engineering research Failure analysis Integral equations Integration Iterative methods Materials testing Reliability theory Service life Statistical tests
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